Cheetah Mobile Q1 2026 Earnings Call - Robotics Revenue Surges as AI Agent Strategy Gains Traction
Summary
Cheetah Mobile reported a strategic pivot in Q1 2026, with robotics and cloud/AI infrastructure revenue now accounting for over half of the company's total. The management team emphasized that true value lies not in general-purpose models but in vertical applications and real-world data accumulation from deployed robots. CEO Fu Sheng argued that the physical world is orders of magnitude more complex than digital environments, making practical deployment and customer feedback loops the primary competitive moat.
Financially, Cheetah Mobile maintained a stable top line at RMB 259 million while its core internet services business continued to generate steady cash flow. The company's AI infrastructure segment grew significantly on a year-over-year basis, reflecting strong enterprise demand for multi-cloud AI management solutions. Management remains cautious about near-term profitability in the robotics segment but highlighted narrowing losses and growing commercial traction with global partners.
Key Takeaways
- Robotics revenue surged 175.9% year-over-year to RMB 51.2 million, representing nearly 20% of total Q1 2026 revenue.
- Cloud and AI infrastructure services grew 68.3% year-over-year, driven by enterprise demand for multi-cloud token management and AI deployment tools.
- Total company revenue remained stable at approximately RMB 259 million despite headwinds in the advertising agency business due to overseas policy changes.
- The robotics segment's adjusted operating loss narrowed by 57.1% year-over-year as operational efficiency improved and commercial deployments scaled.
- CEO Fu Sheng emphasized that real-world deployment data is the primary competitive moat for robotics, arguing that physical environments are exponentially more complex than digital simulations.
- Cheetah Mobile launched a smart wheelchair product in May, targeting elderly mobility and demonstrating how existing robot navigation technology can be adapted for consumer healthcare applications.
- Cloud and AI infrastructure token usage exceeded 400 billion daily average tokens by May 2026, up over 20 times from the start of the year.
- Management expects high-growth segments (robotics and cloud/AI) to exceed 50% of total revenue in H2 2026 as the company transitions away from traditional internet advertising reliance.
- Cheetah Mobile maintained a strong balance sheet with $186 million in cash and over $100 million in long-term investments, providing runway for continued AI and robotics R&D.
- The CEO dismissed near-term commercial viability of humanoids, advocating instead for specialized wheel-based robots that can accumulate vertical data before attempting generalized forms.
Full Transcript
Operator: Good day. Welcome to the Cheetah Mobile first quarter 2026 earnings call. All participants will be in listen-only mode. Should you need assistance, please signal a conference specialist by pressing the star key followed by zero. After today’s presentation, there will be an opportunity to ask questions. To ask a question, you may press star then 1 on your telephone keypad. To withdraw your question, please press star then 2. Please note this event is being recorded. I would now like to turn the conference over to Cheetah Mobile Investor Relations, Helen. Please go ahead.
Helen, Investor Relations, Cheetah Mobile: Thank you, operator. Welcome to Cheetah Mobile’s first quarter 2026 earnings conference call. With us today are our company’s Chairman and CEO, Mr. Fu Sheng, and our company’s Director and CFO, Mr. Thomas Jian. Following management’s prepared remarks, we will conduct the Q&A section. Please note that the management’s script will be presented by an AI agent. Before we begin, I refer you to the safe harbor statement in our earnings release, which also applies to our conference call today, as we will make forward-looking statements. At this time, I would now like to turn the conference call over to our Chairman and CEO, Mr. Fu Sheng. Please go ahead, Fu Sheng.
Guang Kang Jian, Analyst, Guohai Securities1: 2026 remains an important transition year for Cheetah Mobile. We are continuing to evolve from a traditional internet company into a company focused on AI-enabled applications for AI agents and robotics. More importantly, we believe we are gradually moving from capability building into early-stage commercial validation. Our focus is not only on developing AI capabilities, but on turning these capabilities into practical products for real business scenarios, helping customers deliver better ROI. Starting from this quarter, we are separating our robotics and others business into an independent reportable segment. In the first quarter, revenue from robotics and others business increased 176% year-over-year to RMB 51 million, approaching 20% of total revenue. At the same time, adjusted operating loss from this segment narrowed by 57% year-over-year. Customer demand remains strong. We expect robotics and others revenue to grow strongly in 2026.
In Q2, our robotics and other revenue will continue growing on both year-over-year and quarter-over-quarter basis. Today, our robotics business mainly focuses on commercial scenarios with real customer demand and clear long-term value, including reception, guided tours, and intelligent service applications. Our smart personal mobility is another important step for us. This product extends our robotics and AI capabilities into personal mobility and healthcare-related scenarios. More importantly, it further validates that our robotics platform can extend beyond commercial service robots into broader consumer applications. We are encouraged to see recognition from leading industry partners. During the second quarter, we started initial product shipments to a top global designer and manufacturer of mobility products, as well as a leading elderly mobility scooter manufacturer in China. We are seeing encouraging early market feedback and initial commercial traction. Moving to our agent. We are seeing strong customer adoption.
We work closely with Google Cloud and AWS, helping enterprises serving international markets access AI models and use multi-cloud environments more efficiently. In 2026, revenue from our cloud and AI infrastructure services as a part of global enterprise service revenue increased 68% year-over-year, contributing 18% of total revenue. Daily average token usage has increased more than 20 times since January 2026, exceeding 400 billion in May. We expect this revenue growth to continue. We also kept building EasyFlow. It’s early, but we believe it will help customers deploy AI agents and boost productivity.
The two fast-growing businesses, namely robotics and others, as well as cloud and AI infrastructure, already accounted for 38% of our first quarter revenue, and we expect their revenue growth and revenue contributions to continue growing in the coming quarter and to exceed more than 50% of our total revenue in the second half of this year. During the quarter, revenue from our advertising agency business within the global enterprise services segment was affected by policy changes from certain overseas advertising platforms. We believe this revenue decline was primarily driven by external factors rather than changes in customer demand. This was the primary reason for the company’s widening year-over-year operating loss in the first quarter. Our internet services business continues to provide important profit and cash flow support for the company. In the first quarter of 2026, our internet service business generated approximately 15 million RMB in adjusted operating profit.
In 2026-
Operator: Excuse me, there has been an interruption. Just one moment, please.
Guang Kang Jian, Analyst, Guohai Securities1: Profit and cash. While ad agency revenue was hit by policy changes, which impacts our financial results in the near term, it is a stronger base for growth. Moreover, our $186 million cash also supports our AI agents and robotics growth. Thank you.
Thank you, Fu Sheng. Hello, everyone, and thank you for joining us. Unless otherwise stated, all financial figures presented in RMB. During the first quarter of 2026, we continued focusing on operating discipline, improving revenue quality, and maintaining financial flexibility as we invest in AI and robotics initiatives. Total revenue remained relatively stable year-over-year at RMB 259 million during the quarter. While internet service revenue declined due to continued weakness in online advertising, the quality of our revenue mix continued improving. Within the internet service segment, revenue from internet value-added services continued to grow steadily at 8.2% year-over-year, contributing 72.8% of segment revenue. Within a larger portion from internet value-added services, our internet service revenue is becoming increasingly predictable.
More importantly, the internet service business remained profitable and continued generating stable cash, which provides an important financial foundation for our long-term AI and robotics investments. Turning to our robotics and other segments. Starting from this quarter, we began reporting the robotics and others business as a separate segment to present the operating progress of this business. Historical results previously reported under AI and others are now presented as robotics and others as well as global enterprise services. During the first quarter, revenue from robotics and others increased significantly year-over-year, with revenue increasing 175.9% year-over-year to RMB 51.2 million, accounting for 19.8% of total revenue. Adjusted operating loss from this segment narrowed by 57.1% year-over-year, reflecting continued improvement in operating efficiency and commercial execution. Turning to global enterprise services.
This business remains strategically important to the company. In addition to profitability contribution, it provides us with valuable enterprise customer relationships, overseas operating experience, and real-world deployment scenarios for AI-related services. During the quarter, revenue from the advertising agency business was affected by policy changes from overseas advertising platforms, which impacted year-over-year segment revenue performance. However, revenue from our cloud and AI infrastructure services business increased by 68.3%, supported by increasing enterprise demand for AI-related cloud and token management services. Turning to profitability. Operating loss was RMB 28.3 million during the quarter, compared with RMB 26.5 million in the same period last year. The increase mainly reflected lower profitability from the internet and global enterprise services business, following revenue declines in online advertising and advertising agency services, as well as our continued investment in AI and robotics initiatives.
More importantly, both the internet service and the global enterprise services business remained profitable during the quarter. The internet service business generated approximately RMB 15.2 million in adjusted operating profit, while global enterprise services generated approximately RMB 13.8 million in adjusted operating profit. We also maintained a strong balance sheet. As of March 31, 2026, we had approximately $186 million in cash and cash equivalents, as well as over $100 million in long-term investments. We believe our financial position provides sufficient flexibility to continue investing in AI and robotics with a disciplined and sustainable approach. Looking ahead, our financial priorities remain consistent. A, maintaining operating discipline. B, improving revenue quality and operating efficiency. C, supporting long-term investments while preserving financial flexibility.
Overall, we believe the company continues moving toward a more sustainable and balanced operating structure as our AI and robotics businesses gradually scale. Thank you. We are now ready to take your questions.
Operator, we are able to take questions.
Operator: We will now begin the question and answer session. To ask a question, you may press star then one on your telephone keypad. If you are using a speakerphone, please pick your handset.
Helen, Investor Relations, Cheetah Mobile: Hello, operator, can you hear us?
Operator: Yes, I can.
Helen, Investor Relations, Cheetah Mobile: We are now ready to take questions.
Operator: Yes, again, we will begin the question and answer section. To ask a question, you may press star one on your telephone keypad. If you’re using a speaker phone, please pick up your handset before pressing the keys. If at any time your question has been addressed and you would like to withdraw your question, please press star two. At this time, we will pause momentarily to assemble our roster. The first question comes from Thomas Chong with Jefferies. Please go ahead.
Thomas Chong, Analyst, Jefferies: 晚上好,谢谢傅总接受我的提问。最近我们看到市场上越来越多关注机器人智能化能力的提升,很多业内人士认为,真正有价值的不仅是训练阶段的数据,更是在真实部署过程中持续产生、回流并不断优化系统的数据。想问猎豹在过去几年已经是在多个商业场景中长期运营机器人,从你的观察来看,这些运行过程中不断积累的动态的数据对于机器人能力的提升的重要性体现在哪些方面?未来这类数据是否有机会成为推动更通用机器人能力发展的重要的基础?谢谢。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 好的,我来回答。感谢Thomas的提问,我觉得你也点出了机器人行业一个非常重要的问题,就是今天的训练数据不够的问题。AI的高速发展使得我们对机器人行业都有非常高的憧憬,认为今天的AI的agent能力增强了,机器人应该很快就能够去实现各种行为的能力。但事实上我认为并不是这样的,因为AI agent的发展,包括大语言模型的发展,事实上是建立在互联网发展了二三十年的基础上,也就是互联网本质上是形成了大语言模型的基础的训练数据,是一个非常优质的数据集。而机器人行业今天最大的问题是没有数据。今天很多厂商都在想办法用训练数据,包括数据迁移、模拟训练等等。但是有一个很严重的问题是物理世界比实验室环境,比模拟器环境要复杂得多得多得多。所以今天无论是数据的迁移也好,包括采集也好,真正要迁移到不同的本体上,它的适应性实际上是一个非常大的难题。我举一个例子,就是你看今天特斯拉的FSD已经非常不错了,但事实上一些老一点版本的特斯拉自己的汽车都不能装最新的FSD。所以的确数据是个非常大的难题。我也是非常认可你说的,就真实部署环境中持续产生的数据实际上对机器人行业是非常重要的。我们自己的经验来看,比如说我举两个方面的例子,一个方面就是说我们在不同环境下的语音交互能力,实际上是跟我们长期以来在各个场景下,不同的噪音、不同的环境,多人等等这个情况下,做了一些数据的优化和训练是有关的。所以我们的交互机器人的交互的效果,包括接待这些,今天在行业内的性能都是不能吹啊,但是这的确是排在前面的,在行业内有我们自己的口碑的。还有一个例子就是机器人的移动能力。一个非常简单的机器人从A点到B点的这种室内导航,实际上它就类似于一个小型的低速的无人驾驶。如何用便宜的芯片和传感器去实现在不同的环境下的很好的通过能力和避障能力,实际上这都是要在之前我们有大量这种数据的基础上才能做得好的。我们最近推出了一款智能轮椅,刚才我们也讲了一下,其实我们是5月份正式开始量产,开始推向市场,现在看起来在海外,尤其欧洲的销售势头是挺不错的。其实像这种能够在一个传统的轮椅的这么一个产品上做到避障,能够类似于辅助驾驶这种能力,很多厂商,包括一些创业厂商都想做,但想要做出一个原型和真正做到在很多环境下都能做到很好的通过能力,实际上是需要挺多努力的。这和我们多年以来在很多环境当中部署了很多机器人,在无论是什么样的地面条件,比如地毯、地板,包括要增加一些墙壁的反射这些东西,都是经过大量积累的。还有在不断的算法优化,根据实际的场景做算法优化,所以我们这款轮椅真正能够实现较低成本的、高度的可辅助的这种驾驶性能,也在市场上得到了很好的反馈。所以我们觉得今天所谓通用机器人的能力发展,我一直认为就是得一步一步地积累,更好的方式是从实际场景当中拿到数据,然后一点点积累,把一个一个能力逐步地真正实现可落地,才能真正地实现更好的商业化。所以我们是高度看重这一点的。其实包括也有人问过,我们为什么要推像智能轮椅这样的产品,因为在我们眼里,它本质上就是一个能移动的,相当于是机器人,只是载人。所以也是我们机器人战略的一部分。好,谢谢你的提问。
Thomas Jian, Director and CFO, Cheetah Mobile: Operator, can we move to the next question?
Operator: Yes. The next question comes from Vicky Wei from CITIC Securities. Please go ahead.
Thomas Jian, Director and CFO, Cheetah Mobile: Vicky, are you on the line?
Operator: Okay, we’ll go to the next question. The next question comes from Lydia Lin from Morgan Stanley. Please go ahead.
Lydia Lin, Analyst, Morgan Stanley: 谢谢傅盛接受我的提问。我想问的就是,因为过去几年市场对于AI行业的关注度主要是集中在模型能力和模型厂商上,但最近有越来越多的投资者开始关注推理的效率,然后资源的调度以及AI infra层的一些价值。那想问一下,从管理层的观察来看,未来AI产业链最大的价值捕获者更有可能会集中在哪一层?是模型层、基础设施层还是应用层?以及原因是什么?谢谢。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 这是一个很大的产业观察,我的意见仅供参考。我认为未来长期来看,最终的产业链的最大价值捕获者还是会来自应用层。虽然这两年,尤其今年以来,大模型和基础设施层大家都特别受关注,因为我认为本质上是有一个说法叫碳基经济向硅基经济迈进当中,底层建设不够,这个建设在一段时间内是非常稀缺的,所以会有这么大的一个缺口,所以这个阶段肯定价值链是在这方面。但是我想说,第一个,为什么我认为不是模型层呢?因为虽然模型各种竞争很激烈,但是现在我们看到的情况就是模型的差距拉得并不是太开,不容易拉开。今天比如中美的模型,我们认为大概是半年左右的差距,这个差距大概也就是这么一个过程,也没有哪一方把对方拉开,然后大厂商之间的差距,我觉得是有点此消彼长的意味。当然今天模型也是处在很早期,未来我会觉得随着推理芯片、训练芯片不断地去增产,它的训练成本也会逐渐下降。所以我认为模型层会是一个基础设施,但是长期来说,它不会是一家独大的。而且由于模型的能力不断提升,现在可以看到很多模型,即便不是一些顶级模型,在适配一些日常任务的时候,其实它已经实现了非常好的表现了。也就是说,比如说今年中国一些开源模型在调用量上大幅度提升,我觉得最核心的就是它性价比非常好,在一些任务的完成度已经非常高了。甚至我认为,在未来各种专业化的模型还是会不断地涌现,当然这需要一些时间。第二个基础设施层,我们不完全参与,但是我们也看到,因为我们自己有巨云的业务,我们有token的客户在这边消耗,增长也非常快。还是那句话,我觉得这是这个阶段的一个供应和需求不匹配的状态,但是最终基础设施也会进入一个规模经济。而应用,今天实际上AI是可以重塑所有几乎的应用,所以今天的应用层是有巨大的机会的。无论是我们自己在做像机器人这样的产业,我们也做了很长时间了,但是我们还是非常坚定地看好,当模型的能力不断提升,机器人的适用度更加广泛的时候,这也有很多说,就说它可能是比汽车还要大的产业。然后软件层面也有非常多的机会,这里就不摊开来讲了。即便今天我们看一些大模型公司,它估值很高或者很出色,其实它也在某个应用上真正地做深了。比如像Anthropic,它的边缘层,它的Claude Code的崛起,实际上它也是一种应用,它的应用就是写代码的应用,它把写代码这个应用做得足够好,而不是只是提供API让你调用,而是它那个AI agent做得足够好。包括今年年初崛起的像OpenCloud,我们也做了我们EasyFlow这样的产品,所以我觉得应用层还是有非常广阔的天空和机会的。好,谢谢。
Thomas Jian, Director and CFO, Cheetah Mobile: Operator, can we move to the next question?
Operator: The next question comes from Vicky Wei with Citi. Please go ahead.
Vicky Wei, Analyst, Citi: 管理层晚上好,谢谢接受我的提问。我也想请教您关于机器人行业的,就是市场对于未来的竞争格局有很多讨论,比如说有人觉得模型能力是决定性因素,有人觉得是场景运营,或者是
长期部署过程中形成的技术闭环,您认为未来机器人最核心的竞争壁垒是啥?哪些能力最难被复制?谢谢。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 从我今天自己我们对机器人行业理解来说,我认为短期内或者可见的三五年内出现一款特别通用机器人的可能性是非常非常低的。这里面既受制于所谓模型能力,也受制于整个硬件的产业链。像硬件产业链的更新,实际上它的速度相对是比较慢的,而且它只有一些最基础的物理还有材料的物理定律,还有材料的底层的逻辑在里面。所以我今天会认为未来机器人行业最核心的竞争壁垒还是在这个真正的场景运营能力和客户网络上。如果今天我们能够有足够多的场景,有很好的客户网络,使得我们的产品真正被这些场景用起来,我们就能积累出我们自己独有的,无论是经验还是数据。然后刚刚我在第一个问题已经回答过了,就是我们可以针对它去做优化,而这个优化又使得这个产品能够以更好的性价比去真正地符合用户的需要。机器人行业非常火,但是真正在商业落地的时候,其实客户并不关心你是机器人还是一个机器,或者是一个人,他更关心的就是性价比,ROI投入产出。这在我们这几年的运营当中已经非常非常显著地体现出来了。所以即便无论是在媒体当中看到很多机器人很惊艳,但你会发现它真正在实际场景落地当中还非常非常少。而不经过实际场景落地,这一点上我还是重申一下,就机器人在物理环境当中的运营,无论是动作还是工作,它的复杂度其实比汽车的自动驾驶是要高得多的。所以这里面还是复杂度非常高的情况下,我更认为今天能够在实际的运用场景当中,在场景的运营和客户网络当中能形成一个垂直的能打穿的点,比一个泛化的所谓的通用型的机器和模型会重要得多。因为今天我不认为泛化的模型和机器能够迅速地去完成这些垂直场景里所需要的这个ROI。谢谢。
Thomas Jian, Director and CFO, Cheetah Mobile: Operator, please move to the next question.
Operator: The next question comes from Nancy Lu with JP Morgan. Please go ahead.
Nancy Lu, Analyst, JP Morgan: 谢谢管理层接受我的提问。我们看到最近基础模型能力趋同与API成本持续下降,正在推动底层模型加速商品化。那么当企业普遍采用多模型策略,不再依赖单一模型的供应商时候,AI native的产品的竞争焦点已经从模型性能转向模型应用。那么我想请问,未来企业级AI市场中不可替代的稀缺能力究竟存在于哪个层级?以及未来企业级AI产品最终的护城河可能在哪里?谢谢。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 我觉得这是一个很泛的问题。我觉得企业级AI产品最终的护城河应该来自于对用户需求的深度的理解和对这个行业的深度的理解,然后形成了一个超高化的组织能力。因为今天你讲的这几点我觉得也都是现实,就是模型本身的这个能力看上去此消彼长,然后这个性价比也越来越被提出来。所以今天本质上是什么呢?就是它实际上是让企业节约了大量过去耗费在非商业洞察、用户洞察的精力,去节约到真正的去洞察用户需求方面。所以真正的护城河就是来自于你对用户需求的敏锐的洞察,然后快速地推出你的产品和服务,并且改善你的产品和服务。所以我们经常讲这个AI native组织,它的本质就是用AI去重构企业内部的组织流程,而且能够快速地高效地实现企业的运作,能够更高效、更快速去推出自己的产品和服务。比如举个例子,如果你们注意观察,我们其实这一年多推出的各种产品服务比过去多得多,也快得多,但是我们的研发的费用的投入,从费用角度而言,我们是减少了很多的,虽然还有进一步提升的空间,这也就是一个例子。那你这么快速地推出产品和服务,你真正的护城河在哪里呢?是来自于用户的需求,就是你能够真正找到用户需求,并且快速地去推出,而且快速根据用户需求去推出。顺便打个广告,我们也推出了对企业版的AI native组织构建的相应的一些服务和课程,也是把我们的一些经验推给我们的客户。现在已经有些大客户开始签单,然后也开始了这个运营实施。因为商业的竞争的本质就是效率,还有就是对用户需求的洞察。我觉得AI的产品实际上是加速这两个点的到来。好,谢谢。
Thomas Jian, Director and CFO, Cheetah Mobile: Thank you. Operator, please move to the next question.
Operator: The next question comes from Gigi Zhao with GF Securities. Please go ahead.
Guang Kang Jian, Analyst, Guohai Securities0: 你好,管理层您好,那么刚刚您也提到了围绕企业级AI项目,公司有所投入。那我们想了解一下目前大量的企业级AI项目仍然是依赖定制开发和人工服务,距离传统的SaaS产品的标准化交付模式还有一定的一个距离。那么随着AI agent的能力不断提升,您认为AI应用最终是会走向更标准化的SaaS模式,还是会长期保持软件加服务的混合模式?在这一过程中,最关键的变化是什么?
Fu Sheng, Chairman and CEO, Cheetah Mobile: 我觉得今天之所以还有这么大的定制开发和人工服务量,一个很核心的原因是因为AI还处在早期。我们虽然大家都在朋友圈或者是各种媒体上看到AI Native、全员AI,但事实上,绝大部分人对AI的理解和使用还是不够的。我觉得今天只有少数的人能够真正地把AI给很好地用起来,所以这就是一个断代。也就是说今天AI的项目到一个,比如说有历史的企业里,那么它就得针对这个历史做定制开发和人工服务。而传统的SaaS已经发展很多年了,它把很多东西浓缩在代码里面,所以看上去在很多情况下属于标准化的交付。我觉得随着大家对AI的逐步的理解,应该说全员、整个从业者对AI应用的不断的熟练,这个服务模式的比重会不断地下降。在我们公司内部已经实现了全员都在用AI写代码这么一种模式,然后我们内部的一些系统也开始用AI,由业务部门直接去写了,而不再依赖于SaaS软件和服务部门。所以这个过程中最关键的变化,我觉得一方面,我觉得模型能力不断在增强。比如说我们今年一个非常重要的体感,就是今天业务部门再去写内部的一些软件和服务的,用模型的时候,感觉模型能力比去年已经提升了很多。很多以前可能更多是一个demo或者演示级的产品,现在内部已经可以用起来了,那模型能力会不断增强。再一个就是,我们今天的组织结构还是建立在传统的这种工业软件的基础上的。我觉得随着新兴企业的不断的出现,新的AI Native组织不断出现,传统的标准化的SaaS模式,我的观点是会被打破的。所以我们今天给我们的客户提供的,也不再是像传统的这种交付这类型的服务,而是更多的是通过对我们客户员工的培训,还有AI能力的考核,去帮助他们做AI组织的转型。我觉得这个变化是最关键的,也就是说企业要根据AI去改变自己的组织结构和对员工的要求。谢谢。
Guang Kang Jian, Analyst, Guohai Securities0: 好的,感谢傅总精彩的解答。我这边是国联民生证券的赵志远,我这边问题了解。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 好,谢谢。
Thomas Jian, Director and CFO, Cheetah Mobile: Thank you, Zhao. Operator, please move to the next question.
Operator: Thank you. The next question comes from Hupeng Tao with Guotai Haitong. Please go ahead.
Hupeng Tao, Analyst, Guotai Haitong: 好的,管理层晚上好,非常感谢接受我的提问。我想请教一下,因为现在对于人形机器人的关注度比较高,但是从实际的商业化的角度来看,其实轮式的机器人,还有机械臂,依然是现在部署规模最大、商业落地最成熟的形态。我想请教一下管理层,傅总您怎么看未来几年不同机器人形态的发展的节奏?谢谢。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 我关于人形机器人的观点,我觉得我已经在媒体层面表达非常清楚了。我认为人形机器人在可见的这个三五年内都很难实现真正的除了表演之外的商业化进展。也就是说,无论在工厂,在服务行业,甚至包括进家庭,我觉得人形机器人应该说难度相当之大。我们自己有轮式机器人和机械臂,有Factory的XM产品,对吧?我们的机械臂产品其实这几年都在稳步的增长,而今年这个Q1也增长了不错。然后轮式机器人也可以看到,它的适用面、性价比,还有包括今天的室内导航技术,都已经到达一个成熟的点了,所以我认为它也会快速生长。我觉得我的观点一直是这样,我认为机器人应该是从一个一个专业化的叫垂直场景的机器人,不断地去生长,然后去收集数据,当它发展得足够好的时候,它再会不断地融合,慢慢地走向一个比较更具通用形态的机器人形态。而至于双足本身,我觉得在绝大部分场景是不需要的,也没有必要去增加这样的成本和复杂度,包括它的可靠性。所以这就是我的观点。而且我们也再三重申了,我们做机器人最关心的就是商业化落地,是真正的能被市场买单,而且是真正的市场主体买单,而不仅仅是一些项目落地,或者说一些集成项目。所以我觉得轮式机器人到了未来慢慢再配上B这么一个产品形态,会在很长一段时间内是人形机器人发展的主力形态。谢谢。
Thomas Jian, Director and CFO, Cheetah Mobile: Operator, please move to the next question.
Operator: Thank you. The next question comes from Guang Kang Jian with Guohai Securities. Please go ahead.
Guang Kang Jian, Analyst, Guohai Securities: 好的,谢谢傅盛先生接受我的提问。我想问一下,家庭服务机器人被认为是机器人行业长期最大的一个市场,但同时也是需求最复杂、技术挑战最高的一个场景。猎豹这个季度也推出了自己的一个智能轮椅产品,你认为未来两到三年内,家庭机器人最有可能率先实现突破的一个应用方向是什么?然后行业距离真正大规模普及还需要哪些门槛去跨越?谢谢。
Fu Sheng, Chairman and CEO, Cheetah Mobile: 对,其实家庭机器人是个很泛的概念,你要真讲家庭机器人已经突破的就是扫地机器人,它也叫robot,对吧?但如果我们把它考虑成一个能和成年人一样干繁重任务的,我认为第一个,就是我们之所以做智能轮椅,因为在我们的观点里,智能轮椅就是一款机器人。只不过以前我们的机器人送货,智能轮椅其实你也可以理解成在送人。我认为家庭落地,一个就是移动能力,从A到B的移动能力;第二个是在移动的能力上增加一些额外的能力,比如扫地机器人是增加扫地能力。我们现在看到的就是陪伴,还有就是帮你去实现家庭的一些控制,用语音的方式做控制,把它融合到机器人里,帮你做一些规划,做很好的陪伴,实际上都是一个方向。反正我们的轮椅产品也是有这样的一些功能的,包括在我们的APP里也很快会推出和老人的陪伴的功能。我觉得如果像大家想象的做家务这样的能力,我认为两到三年内是不可能实现的。因为我们自己有机械臂公司,我们的机械臂在很多场景,无论是工业场景、商业场景,甚至也有我们的客户买去做商业洗碗这样的场景,我们都看过这样的案例。今天大家知道,接触物理世界对于机器人来说是极度复杂的,它真正的复杂不来自于能做出一些动作,而是做出一些动作以后的稳定性和成功率。今天哪怕抓一个杯子,这样的成功率没有一家能做到100%,哪怕是在一个厨房环境当中去抓取一个杯子。但是作为家庭应用来说,你抓取这个杯子,哪怕是99%的成功率,你也会每一段时间就摔杯子,实际上它带来的负面效果是非常大的。更不要说如果是人形进家庭,它有摔倒的问题,砸到东西的问题,砸到人的问题,还有就是它的质量的可靠性问题。一个家电你买回去大概几年的质量都是没问题的,今天你真正要做一个复杂的机器人,在很长的一段时间内,质量能保证不坏,今天对于很多机器人公司都是一个难题。所以我觉得家庭机器人,我们应该务实一点,我们的观点就是能够真正地实现家庭的陪伴,能够实现一些老人、残障人士的移动,我觉得就是一个很好的应用突破方向。好,谢谢。
Thomas Jian, Director and CFO, Cheetah Mobile: Okay, operator. Please check if they have further questions. If not, then we will end this call.
Operator: Thank you. Seeing there are no further questions. This concludes both our question and answer session and today’s conference. Thank you for attending today’s presentation. You may now disconnect.
Thomas Jian, Director and CFO, Cheetah Mobile: Thank you. Bye bye.
Guang Kang Jian, Analyst, Guohai Securities: Thank you.